There are many potential military and commercial applications for an improved magnetic sensing system that can more effectively and rapidly detect the presence of a magnetic object, locate its position in space, and classify the object in terms of the magnitude and direction of the source of its “magnetic anomaly field”. In particular, there is a need for improved passive magnetic sensing systems that can perform Detection, Localization and Classification (DLC) of magnetic objects (or “targets”). Magnetic anomaly fields emanate from the “magnetic moments” (or signatures) that are produced by the ferrous materials (e.g., iron, steel, etc.) that are contained in the physical structure of a target. The magnetic field of a target produces localized spatial distortions (i.e., “anomalies”) in the otherwise relatively constant Earth's background magnetic field. At distances from a target that are more than two or three times the target's longest dimension, its magnetic anomaly field can be mathematically described by the well known magnetostatic dipole equation. The dipole equation relates the spatial variations of the anomaly field of a magnetically polarized object to the object's vector magnetic dipole signature. Conversely, measurements of an object's magnetic anomaly field can be used in conjunction with the dipole equation (or its spatial gradients) to determine the object's location and its magnetic dipole signature. The magnitude and direction of a target's magnetic signature depends on the orientation of the target's ferrous materials with respect to the Earth's field and also on the size, geometry and magnetic permeability of the ferrous materials. Thus, in principle, magnetic sensor systems can perform DLC of magnetic objects by detecting the presence of a magnetic anomaly field, determining the location of its source, and classifying the object in terms of its magnetic signature.
In general, targets of interest can include stationary objects such as buried explosive mines and/or other unexploded ordnance. Mobile targets of interest include naval vessels and land vehicles such as cars, trucks or military tanks. For stationary targets, the magnetic sensing based system should be capable of performing effective DLC while the sensing platform is in motion. For mobile targets, the sensing system should be able to function well while stationary. However, for many important sensing applications, the system should be able to perform effective DLC while both the target and the sensing system are in motion.
An optimally effective magnetic sensing system should be capable of performing nearly instantaneous (i.e., “real-time”) DLC of both mobile and stationary targets. In particular, the sensing system should be capable of measuring a complete set of DLC parameters (e.g., target range, bearing and magnetic signature) at any sensor position within detection range of the target. Furthermore, the sensing system should be able to discriminate or differentiate between the magnetic signature of a target of interest and magnetic anomaly fields due to non-target-type magnetic objects (i.e., “magnetic clutter” and/or magnetic noise from geologic sources) that may lie within the detection range or field-of-view of the sensor system. Thus, an effective magnetic sensing system should be capable of “point-by-point” DLC of magnetic targets with minimal delay between the sensor's detection of a magnetic target and its output/display of target localization and classification data.
Accurate detection, ranging and classification of magnetic objects usually requires a number of vector magnetic sensors that are configured as magnetic tensor “gradiometers”. A gradiometer measures “magnetic gradients”, i.e., rate of change of magnetic fields with distance. It is known in the art that conventional gradiometers can perform point-by-point DLC of a magnetic dipole target by using a magnetic sensing system that measures five independent gradient tensor components and a set of vector field components of the target's magnetic anomaly field. However, limitations of conventional approaches have limited the development of magnetic gradiometry to experimental devices that do not appear to be practical for general DLC applications. The limitations of prior art conventional tensor gradiometers include the following:                Localization methods that are rather complex, computationally intensive and difficult to implement in a cost effective and easily deployable system.        Requirements for sensor platform motion to be impractically constrained to be along nearly constant velocity straight-line paths with very little change in sensor platform orientation.        A DLC response that may be too slow for cases where there is fast relative motion between sensor system and target.        Accuracy that may be reduced if the target's magnetic signature changes with the target's motion.        Data sets that do not allow development of an optimal target discrimination capability for cases where the magnetic signature of a target of interest is convolved with non-target-related magnetic anomalies such as magnetic clutter and/or geologic noise.        
U.S. Pat. No. 6,476,610 (i.e., “the '610 patent” as it will be referred to hereinafter) addressed certain aspects of the limitations of conventional gradiometry. Briefly, the '610 patent disclosed a novel magnetic gradiometer and signal processing approach based on a “scalar triangulation and ranging” (STAR)” concept for target localization from maneuverable sensing platforms. The STAR method uses unique, rotationally invariant scalar “contractions” of magnetic gradient tensor components to “triangulate” relative distances to a target. Within the target-detection distance of a STAR-type gradiometer, the scalar triangulation process does not directly depend on the direction or magnitude of a target's magnetic dipole signature.
More recently, U.S. Pat. No. 6,841,994 (i.e., “the '994 patent” as it will be referred to hereinafter) disclosed significant improvements to the STAR design and method that allow better measurements of the range, relative bearing and magnetic signature of stationary targets from mobile sensing platforms. Still more recently, U.S. Pat. No. 7,342,399 (i.e., “the '399 patent” as it will be referred to hereinafter) discloses improved STAR-type magnetic sensing-based means and methods for real-time tracking of a moving magnetic target and for reducing certain “asphericity errors” that are inherent to the STAR DLC method. The above-noted patents successfully address several of the above-mentioned limitations. However, these prior art magnetic sensing systems still have the following limitations:                DLC methods that preferentially involve physically pointing a particular sensor system axis at the target, i.e., they require means and methods for mechanically orienting a sensor. However, the need for an orientation/positioning modality may be undesirable or impractical for some applications.        DLC methods that apply primarily to dipole-type magnetic anomaly fields where the magnetic targets are isolated from other sources of magnetic anomaly fields. However, many magnetic anomaly sensing applications require localization and discrimination of magnetic objects within magnetically complex environments where fields from multiple targets, magnetic clutter and/or geologic noise may be within the field-of-view of the sensor system.        
As disclosed in the above-noted patents, the gradient contraction (CT) of the full, nine-component magnetic gradient tensor of a magnetic dipole target is a rotationally invariant and robust scalar that is independent of gradiometer orientation. The “scalar contractions” that provide the basis for the STAR method and their relation to the multiple target problem will be explained briefly with the aid of FIG. 1 that summarizes the essential geometrical features of the gradient contraction based STAR method for localization and discrimination of magnetic objects.
In FIG. 1, the geometrical features of the magnetic lines of force (or B-field as it is known) surrounding a dipole target T are qualitatively represented by solid lines and contours of constant CT field surrounding target T are indicated by dashed lines. Mathematically, at a given sensor-to-target distance “r”, CT is primarily a function of the magnetic dipole moment M of target T, distance r, and a dimensionless asphericity parameter “k”. The k-parameter characterizes the variance of CT from true spherical symmetry. For media with constant magnetic permeability μ, CT has the form of a slightly aspherical central potential type function. Specifically, CT=k(μ/4π)M/r4 where calculations show that k is an “asphericity parameter” that is a number that slowly varies from approximately 7.3 for points aligned with the dipole axis to 4.2 for points transverse to the axis. Conversely, for contours of constant gradient contraction, the ratio of the diameter on the dipole axis to a diameter transverse to the axis is approximately 1.14 to 1.
The presence of multiple magnetic objects can result in significant overlapping of magnetic anomaly fields. The overlapping fields can distort the topology of contours of constant CT in such a manner that, in some regions (particularly between field sources), the CT contours may not enclose a single field source. Thus, in some regions between multiple sources of magnetic anomaly fields, the prior art STAR methods can be inaccurate.